CN112465833A - Automatic feed detection and supplement method for livestock trough - Google Patents
Automatic feed detection and supplement method for livestock trough Download PDFInfo
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Abstract
The invention discloses an automatic feed detection and supplement method for a livestock trough, which comprises the steps of collecting liquid level images of the livestock trough through a camera, further segmenting the images according to different color ranges and obtaining area areas, and judging whether livestock shielding and the type of current feed occur in a detection area or not; then preprocessing the acquired liquid level image, classifying the image by using an SVM classifier, judging whether the feed in the trough corresponding to the image is sufficient or not, or carrying out image segmentation on the acquired liquid level image, calculating the position of the liquid level of the trough, and further comparing the position of the liquid level of the trough with a preset standard line to judge whether the feed in the corresponding trough is sufficient or not; if the feed in the current trough is insufficient, the discharge hole is controlled to be opened so as to automatically supplement the feed; and returning to carry out image acquisition if the feed in the current trough is sufficient. The invention greatly improves the automation level of the livestock breeding process, reduces the waste of manpower resources and feed and improves the breeding efficiency.
Description
Technical Field
The invention relates to a feed supplement method, in particular to a feed supplement method for a livestock trough.
Background
When people have become worried about no longer being essential for life, they have gradually started to pursue high quality and high levels of eating and purchasing significantly more meat and poultry and other medium and high grade food. As can be known from investigation, the meat purchased by people has the most livestock and poultry meat products such as chicken, duck, pork, mutton and the like, wherein the share of pork is more than 60 percent, and the pork is a main source of meat food materials in life of people, and the consumption habit continues all the time.
At present, certain limiting conditions exist in livestock breeding in China, such as live pig breeding, the traditional trough or cement plate trough is generally adopted by scattered households to manually separate meals and feed dry materials, the mode is mainly based on manual operation and treatment, the breeding scale is relatively small, meanwhile, the automation degree and the modernization degree are low, a large amount of resources and the energy of people are unnecessarily consumed, and various problems of high breeding cost, low breeding efficiency and the like are caused. Compared with the breeding in scattered households, the large-scale breeding mode can effectively reduce the influence of the fluctuation of the pig price on the life of people, stabilize the pork price and protect the benefits of the farmers. Meanwhile, large-scale breeding facilitates the management of live pigs, various diseases can be effectively prevented, and the risk in the breeding process is reduced. Meanwhile, the large-scale breeding can reasonably utilize various production data, improve the use efficiency of resources, reduce the breeding cost by a scientific breeding method and promote the specialization of pig production.
In the large-scale breeding process, how to comprehensively use various modern scientific technologies to improve the overall production level and production efficiency of the breeding industry and how to comprehensively apply technologies such as information technology, artificial intelligence and system integration in the breeding industry so as to improve the automation level of the breeding process of livestock such as live pigs and reduce the waste of manpower resources and feed, thereby reducing the breeding cost and improving the breeding efficiency are urgent to be further researched and solved.
Aiming at the problems, the invention provides and realizes an automatic detection and supplement method for the feed of the livestock trough.
Disclosure of Invention
The purpose of the invention is as follows: in order to overcome the defects in the prior art, the invention aims to provide an automatic detection and supplement method for the feed of the livestock trough.
The technical scheme is as follows: in order to solve the technical problems, the invention provides an automatic detection and supplement method for a feed of a livestock trough, which comprises the following steps:
s1) a camera is set up above the livestock trough, and a discharge hole which can be controlled to open and close is arranged on the livestock trough;
s2) acquiring liquid level images of the poultry and livestock troughs through a camera, further segmenting the images according to different color ranges in a detection area, and acquiring the area of the area, so as to judge whether poultry and livestock shelter and the type of current feed exist in the detection area, and entering step S3 when judging that the type of the current feed is viscous feed, or entering step S4 when judging that the type of the current feed is high-flow feed);
s3) preprocessing the acquired liquid level image, classifying the image by using an SVM classifier, judging whether the feed in the trough corresponding to the image is sufficient or not, and entering the step S5);
s4) carrying out image segmentation on the acquired liquid level image, calculating the position of the liquid level of the trough, further comparing the position of the liquid level of the trough with a preset standard line, judging that the feed in the corresponding trough is sufficient when the position of the liquid level of the trough is higher than the preset standard line, otherwise, judging that the feed in the corresponding trough is insufficient, and entering the step S5);
s5) if the feed in the current trough is insufficient, controlling the discharge hole to open to automatically supplement the feed; and if the feed in the current trough is sufficient, returning to the step S2) to carry out image acquisition work.
Preferably, the kinds of the feed in the step S2) include a viscous type feed and a high fluidity type feed.
Further preferably, when the image is segmented according to different color ranges and the area of the region is obtained in step S2), a method of removing a small-area connected region is used to correct the deviation of the detection result caused by the adhesion of part of the feed to the detection region.
More preferably, the step S4) of performing the liquid level curve correction after the image segmentation includes: and sequentially connecting adjacent edge points and comparing the slopes, and if the slope difference of adjacent straight lines is larger, abandoning the current edge point and connecting the current edge point with the next edge point until a complete contour is formed.
Further preferably, the step S3) of preprocessing the input image and classifying the image by using an SVM classifier includes: after preprocessing the input image of the viscous feed, extracting the edge characteristics of the image outline, and then predicting whether the feed in the trough corresponding to the image is sufficient by using an SVM classifier.
Preferably, the discharge hole capable of being controlled to open and close comprises a discharge hole and a valve module which is matched with the discharge hole and is used for controlling the opening and closing of the discharge hole; the valve module is electrically connected or in communication connection with the camera and the control system.
Preferably, the system hardware of the control system is a raspberry pi.
Further preferably, the step S2) is: acquiring liquid level images of the livestock trough through a camera, further segmenting the images according to different color ranges, and acquiring area of the area so as to judge whether livestock shelter and the type of current feed appear in the detection area; if the detection area is judged to be blocked, continuously collecting the liquid level image of the poultry and livestock trough through the camera and repeating the judgment until the detection area is not blocked; if the detection area is not blocked, the step S3) is performed when the current feed type is determined to be the viscous feed type, otherwise, the step S4) is performed when the current feed type is determined to be the high-flow feed type).
Further preferably, the trough includes a sloped sidewall; the inclined side wall comprises a strip-shaped white inner wall which corresponds to the detection area and extends from top to bottom.
Further preferably, the detection area overlaps with an outer contour of the strip-shaped white inner wall.
Has the advantages that: according to the automatic feed detection and supplement method for the livestock trough, provided by the invention, the images of the livestock trough in the feeding process are processed through image processing and machine learning technologies, and whether the feed needs to be added to the current trough (also called trough) is judged by combining the arrangement of a standard line, so that the purpose of intelligent feeding is achieved.
Meanwhile, the required hardware is the cameras, the valve modules and the raspberry pie, and the plurality of cameras can be controlled to carry out detection simultaneously through the raspberry pie, so that the detection efficiency is further improved, and the detection cost is reduced; and through the mode of combining software and hardware, can use and/or monitor each item data in birds poultry breeding process and carry out process control, further effectively promoted the digitization and the high automation of aquaculture.
Drawings
FIG. 1 is a block diagram of a method for automatically detecting and supplementing the feed of a poultry trough according to an embodiment;
FIG. 2 is a flowchart of SVM based image classification in an embodiment.
Detailed Description
The present invention will be described in further detail with reference to the following examples and drawings, but the present invention is not limited to the following examples.
The present embodiment provides an automatic detection and supplement method for a feed for a poultry trough, as shown in fig. 1, the method includes the following steps:
s1) a camera is set up above the livestock trough, and a discharge hole which can be controlled to open and close is arranged on the livestock trough;
s2) acquiring liquid level images of the poultry and livestock trough through a camera, further segmenting the images according to different color ranges in a detection area (also called a method for extracting regional color features or a color feature extraction method), and acquiring the area of the area to judge whether poultry and livestock shelter and the type of current feed occur in the detection area, wherein the type of the feed comprises viscous feed and high-flow feed; if the detection area is judged to be blocked, continuously acquiring the liquid level image of the livestock trough through the camera and repeating the judgment (namely judging whether the livestock are blocked) until the detection area is not blocked; if the detection area is not blocked, entering step S3) when the current feed type is determined to be viscous feed, or entering step S4) when the current feed type is determined to be high-flow feed;
s3) preprocessing the acquired liquid level image, classifying the image by using an SVM classifier, judging whether the feed in the trough corresponding to the image is sufficient or not, and entering the step S5);
s4) carrying out image segmentation on the acquired liquid level image, calculating the position of the liquid level of the trough, comparing the position of the liquid level of the trough with a preset standard line, judging that the feed in the corresponding trough is sufficient when the position of the liquid level of the trough is higher than the preset standard line, otherwise, judging that the feed in the corresponding trough is insufficient, and entering the step S5); the preset standard line can be flexibly set according to the actual application scene;
s5) if the judgment result obtained in the step S3) or the step S4) is that the feed in the current trough is insufficient, controlling the feed outlet hole to be opened to automatically supplement the feed; and if the feed in the current trough is sufficient, returning to the step S2) to carry out image acquisition.
In this embodiment, the trough includes an inclined sidewall; the inclined side wall comprises a strip-shaped white inner wall which corresponds to the detection area and extends from top to bottom. In this embodiment, the detection area overlaps with the outer contour of the strip-shaped white inner wall. In a practical application scenario, the inclined sidewall may be a side wall of the trough with an upper opening larger than a bottom, or may be a side wall of the trough with one or more portions gradually inclined from top to bottom. The strip-shaped white inner wall can be a square or rectangular strip-shaped white inner wall, or an inner wall pasted with strip-shaped white stickers, which can be spliced on the trough, or can be a part of the integral trough. The above-mentioned detection area corresponds to the strip-shaped white inner wall, that is, the area corresponding to the strip-shaped white inner wall in the acquired image is used as the detection area. It can also be said that: the detection area is an area corresponding to the strip-shaped white inner wall in the acquired image.
In this embodiment, when the image is segmented according to different color ranges and the area is obtained in step S2), the method for removing the small-area connected area is used to correct the deviation of the detection result (or the judgment result) caused by the adhesion of part of the feed to the detection area, so as to effectively reduce the influence of the adhesion of part of the feed to the detection area on the detection result, that is, the deviation of the judgment/detection result of whether the livestock is blocked and/or the deviation of the judgment/detection result of the current feed type is/are effectively reduced, so that the detection result is more accurate.
In this embodiment, in the step S2), it is determined whether the detection area is shielded by the livestock, taking the pig as an example, the feed has different colors, mostly yellow and black, according to the difference between the main material and the auxiliary material, and the color of the animal such as the pig is similar to the color of red, and it is determined whether the pig is in the detection area and occupies a large space according to the areas of the different color areas, so as to determine whether the detection area is shielded by the livestock, if so.
In some embodiments, after the image segmentation in step S4) and before the calculation of the position of the trough liquid level, as shown in fig. 1, the method for automatically detecting and supplementing the feed for the poultry trough further comprises: and sequentially connecting adjacent edge points and comparing the slopes, and if the slope difference of adjacent straight lines is large, abandoning the current edge point and connecting the current edge point with the next edge point until a complete contour is formed.
In this embodiment, step S3) above pre-processes the input image, and performs image classification using an SVM classifier, as shown in fig. 1, specifically including: after preprocessing the input image of the viscous feed, extracting the edge characteristics of the image contour, and then predicting/judging whether the feed in the trough corresponding to the image is sufficient or not by using an SVM classifier.
The SVM classifier comprises an image processing module and an SVM classifier module, wherein an SVM-based image classification process is shown in FIG. 2, firstly, sample images in an image sample database are preprocessed and feature extracted in the image processing module, and then image feature classification, statistics and redundancy removal are carried out, so that image feature data are obtained; and after the SVM classifier module determines the kernel function, determining the type of the SVM classifier according to the extracted image feature data, learning and training image feature samples, testing and decision classification of the image feature samples, and outputting images.
In this embodiment, the discharging holes that can be controlled to open and close include a discharging hole and a valve module adapted to the discharging hole and controlling the opening and closing (also referred to as closing) of the discharging hole, and the discharging holes that can be controlled to open and close are discharging holes provided with the valve module; the valve module is electrically connected with the camera and the control system. In some embodiments, the valve module is communicatively coupled, such as wirelessly, to the camera and control system.
In a practical application scenario, when the discharge hole is controlled to be opened in step S5) to automatically supplement the feed, the time length of opening the discharge hole may be controlled by the control system, such as: the discharge opening is opened to predetermine reinforced time length, closes the discharge opening. The preset charging duration can be flexibly set according to the size of the trough, the size of the discharge hole, the type of the feed and/or the position of the standard line in the actual application scene.
The system hardware of the control system in this embodiment is a raspberry pi.
The viscous feed is liquid with high density, namely liquid with density larger than a preset density threshold value; the high fluidity feed is a liquid having high fluidity, that is, a liquid having a low density, and may be a liquid having a density equal to or less than a density threshold value. The density threshold value can be set according to the actual application scene. The livestock are animals including domestic fowls such as pigs and ducks. The trough is also referred to herein as a trough.
When the method is used specifically, the working principle and the flow are explained by taking the automatic detection and supplement method for the feed of the livestock trough provided by the embodiment as an example when the method is used for a pig trough: firstly, according to the position of a pig feed trough, a camera is built above the pig feed trough, and a valve module is arranged on a discharge hole in the pig feed trough, so that the opening and closing (opening and closing) of the discharge hole are controlled by a raspberry group control system; then acquiring a liquid level image of a pig feeding trough through a camera, transmitting the image to a system, dividing the image by the system according to different color ranges, and acquiring the area of a region so as to judge whether a detection region is blocked by a pig and the type of feed in the trough at present, wherein the type of feed comprises viscous feed and high-flow feed, and different detection methods are used for different feeds; secondly, when judging that the current feed type is viscous feed in the previous steps, preprocessing the input image by using an SVM classifier, and judging whether the feed in the trough corresponding to the image is sufficient or not by using the SVM classifier for image classification, when judging that the current feed type is high-flow feed in the previous steps, dividing the image, calculating the accurate position of the liquid level of the trough, and then comparing the accurate position of the liquid level with a preset standard line which is set in advance, so as to judge whether the liquid level position of the trough is higher than the preset standard line position or not, when the liquid level position of the trough is higher than the preset standard line, judging that the feed in the corresponding trough is sufficient, otherwise, judging that the feed in the corresponding trough is insufficient; if the judgment result output in the previous step is that the feed in the current trough is insufficient, the valve module is controlled by the control system to open the discharge hole so as to automatically supplement the feed, and if the judgment result output in the previous step is that the feed in the current trough is sufficient, the control system returns to the previous step to continue to repeat the image acquisition work. In conclusion, the pig feed trough image in the feeding process is detected by combining image processing and machine learning (SVM), whether the current trough needs to be added with feed or not is judged, meanwhile, the amount of the added feed can be controlled through the position of a standard line in the feed adding process, so that the aim of intelligent feeding is fulfilled, the pig feed trough is detected, and whether the feed needs to be automatically supplemented or not is judged.
According to the invention, the images of the livestock feeding trough in the feeding process are processed through an image processing and machine learning (SVM) technology, and whether feed needs to be added to the current feeding trough/trough is judged by combining the arrangement of a standard line, so that the purpose of intelligent feeding is achieved. Meanwhile, the invention can control a plurality of cameras to detect simultaneously through the raspberry pie, and can use and/or monitor various data in the livestock breeding process to control the process through a software and hardware combined mode, thereby further improving the detection efficiency, reducing the detection cost and further effectively improving the digitization and high automation of the breeding industry.
The above is only a preferred embodiment of the present invention, it should be noted that the above embodiment does not limit the present invention, and various changes and modifications made by workers within the scope of the technical idea of the present invention fall within the protection scope of the present invention.
Claims (10)
1. A method for automatically detecting and supplementing feed for a poultry trough is characterized by comprising the following steps:
s1) a camera is set up above the livestock trough, and a discharge hole which can be controlled to open and close is arranged on the livestock trough;
s2) acquiring liquid level images of the poultry and livestock troughs through a camera, further segmenting the images according to different color ranges in a detection area, and acquiring the area of the area, so as to judge whether poultry and livestock shelter and the type of current feed exist in the detection area, and entering step S3 when judging that the type of the current feed is viscous feed, or entering step S4 when judging that the type of the current feed is high-flow feed;
s3) preprocessing the acquired liquid level image, classifying the image by using an SVM classifier, judging whether the feed in the trough corresponding to the image is sufficient or not, and entering the step S5);
s4) carrying out image segmentation on the acquired liquid level image, calculating the position of the liquid level of the trough, further comparing the position of the liquid level of the trough with a preset standard line, judging that the feed in the corresponding trough is sufficient when the position of the liquid level of the trough is higher than the preset standard line, otherwise, judging that the feed in the corresponding trough is insufficient, and entering the step S5);
s5) if the feed in the current trough is insufficient, controlling the discharge hole to open to automatically supplement the feed; and if the feed in the current trough is sufficient, returning to the step S2) to carry out image acquisition work.
2. The automatic detection and replenishment method of feed for poultry and livestock troughs according to claim 1, characterized in that: the types of the feed in the step S2) comprise a viscous feed and a high-fluidity feed.
3. The automatic detection and replenishment method of feed for poultry and livestock troughs according to claim 1, characterized in that: and in the step S2), when the image is segmented according to different color ranges and the area of the region is obtained, correcting the deviation of the detection result caused by the fact that part of the feed is stuck on the detection region by adopting a method for removing a small-area communication region.
4. The automatic detection and replenishment method of feed for poultry and livestock troughs according to claim 1, characterized in that: the step S4) of performing image segmentation and then performing liquid level curve correction includes: and sequentially connecting adjacent edge points and comparing the slopes, and if the difference between the slopes of the adjacent straight lines is large, abandoning the current edge point and connecting the current edge point with the next edge point until a complete contour is formed.
5. The automatic detection and replenishment method of feed for poultry and livestock troughs according to claim 1, characterized in that: the step S3) of preprocessing the input image and classifying the image by using an SVM classifier specifically includes: after preprocessing the input image of the viscous feed, extracting the edge characteristics of the image contour, and then predicting whether the feed in the trough corresponding to the image is sufficient by using an SVM classifier.
6. The automatic detection and replenishment method of feed for poultry and livestock troughs according to claim 1, characterized in that: the discharging hole capable of being controlled to be opened and closed comprises a discharging hole and a valve module which is matched with the discharging hole and is used for controlling the opening and closing of the discharging hole; the valve module is electrically connected or in communication connection with the camera and the control system.
7. The automatic detection and replenishment method of feed for livestock troughs according to claim 6, characterized in that: the system hardware of the control system is a raspberry pi.
8. The automatic detection and replenishment method of feed for poultry and livestock troughs according to claim 1, characterized in that: the step S2) is: acquiring liquid level images of the livestock trough through a camera, further segmenting the images according to different color ranges, and acquiring area of the area so as to judge whether livestock shelter and the type of current feed appear in the detection area; if the detection area is judged to be blocked, continuously acquiring the liquid level image of the poultry and livestock trough through the camera and repeating the judgment until the detection area is not blocked; if the detection area is not blocked, the step S3) is performed when the current feed type is determined to be viscous feed, otherwise, the step S4) is performed when the current feed type is determined to be high-flow feed.
9. The automatic detection and replenishment method of feed for poultry and livestock troughs according to claim 1, characterized in that: the trough comprises an inclined side wall; the inclined side wall comprises a strip-shaped white inner wall which corresponds to the detection area and extends from top to bottom.
10. The automatic detection and replenishment method of feed for poultry and livestock troughs according to claim 9, characterized in that: the detection area is overlapped with the outer contour of the strip-shaped white inner wall.
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